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This report describes the development of a new theory and methodologies for source studies and the results of applications of various time series analysis methods to seismological analyses of interest in nuclear monitoring. Applying the algorithms and ideas of multi-channel deconvolution to regional Pn and Lg arrivals showed that the concept of signal factorability, decomposition of seismogram spectra into site and source factors, is valid for such data. This enables one to investigate various possible applications using inter-event and inter-sensor transfer functions to detect variations in the locations, source mechanisms, source time functions and azimuths of regional sources. Such techniques make use of the details of regional waveforms and circumvent the problems associated with the extreme variability and unpredictability of regional waveforms and the virtual impossibility of computing realistic Greens's functions theoretically. (edc)

This report describes the development of a new theory and methodologies for source studies and the results of applications of various time series analysis methods to seismological analyses of interest in nuclear monitoring. Applying the algorithms and ideas of multi-channel deconvolution to regional Pn and Lg arrivals showed that the concept of signal factorability, decomposition of seismogram spectra into site and source factors, is valid for such data. This enables one to investigate various possible applications using inter-event and inter-sensor transfer functions to detect variations in the locations, source mechanisms, source time functions and azimuths of regional sources. Such techniques make use of the details of regional waveforms and circumvent the problems associated with the extreme variability and unpredictability of regional waveforms and the virtual impossibility of computing realistic Greens's functions theoretically. (edc)

24 p. ; 27 cm

xxix, 784 s

Includes bibliography

http://uf.catalog.fcla.edu/uf.jsp?st=UF002868868&ix=nu&I=0&V=D

The measurement of regional attenuation Q(1) can produce method dependent results. The discrepancies among methods are due to differing parameterizations (e.g., geometrical spreading rates), employed data sets (e.g., choice of path lengths and sources), and methodologies themselves (e.g., measurement in the frequency or time domain). We apply the coda normalization (CN), two-station (TS), reverse two-station (RTS), source-pair/receiver-pair (SPRP), and the new coda-source normalization (CS) methods to measure Q of the regional phase, Lg (Q(Lg)), and its power-law dependence on frequency of the form Q(Of) with controlled parameterization in the well-studied region of northern California using a high-quality data set from the Berkeley Digital Seismic Network. We test the sensitivity of each method to changes in geometrical spreading, Lg frequency bandwidth, the distance range of data, and the Lg measurement window. For a given method, there are significant differences in the power-law parameters, Q(o) and eta, due to perturbations in the parameterization when evaluated using a conservative pairwise comparison. The CN method is affected most by changes in the distance range, which is most probably due to its fixed coda measurement window. Since, the CS method is best used to calculate the total path attenuation, it is very sensitive to the geometrical spreading assumption. The TS method is most sensitive to the frequency bandwidth, which may be due to its incomplete extraction of the site term. The RTS method is insensitive to parameterization choice, whereas the SPRP method as implemented here in the time-domain for a single path has great error in the power-law model parameters and eta is greatly affected by changes in the method parameterization. When presenting results for a given method it is best to calculate Q(of) for multiple parameterizations using some a priori distribution.

This report explores broadband seismic signal processing aimed at extracting information relevant to several key aspects of nuclear monitoring, yield estimation, source studies and discrimination. The term 'broadband processing' in our definition refers to techniques designed for extracting the maximum information allowed by the S/N ratio from the data, using an information-theoretical definition, not the conventional waveform inversion of the so-called broadband seismograms, and estimating error bounds for parameters estimated. Another recurrent central idea examined and exploited in this report is the frequency-domain decomposition of multi-event, multi-sensor data into source and site factors. Various ensemble-averaged coherence measures can then be used to test the effectiveness of such factorization. In Section 1.0, we examine the spectral factorability of P sub n and Lg phases recorded at NORESS and the 3C subarray of NORSAR. Section 2.0 re-examines some aspects of estimating secondary arrivals (pP, spall, etc.) in teleseismic P waves and applying corrections to Mb. Section 3.0 explores ways to perform spatio-temporal source inversion using waveform data. In the last part of the report we describe an approach for S/N ratio enhancement, using the application of site waveform- equalization, together with adaptive filtering.

In this report we present test results on various non-conventional signal processing approaches as applied to data from regional seismic arrays. In particular, an adaptive approach for automatic identification of regional arrivals was tested to (Der et al 1993). This method was designed to circumvent some difficulties that plagued previous attempts of 3-component polarization analyses for regional arrival identification. In particular, the methodology is designed to avoid complications due to signal distortion by near sensor geology and complex arrivals made up of superpositions of multiple independent signal components. The idea is to replace time delay operators and assumed particle motion patterns used in deterministic signal processing with empirically computed sets of transfer functions using a learning set of relatively high S/N events. The application of this approach requires more than three sensor outputs (such as a 3-component combination plus some extra array sensors). We have tested both a frequency domain and a time domain approach to this algorithm. Thus far the frequency-domain version has reached a further stage of development. The methodology appears to be an attractive alternative to conventional array processing methods in quickly identifying and discriminating various arrivals from the same source region, or similar arrivals from different source regions at a small array. We are also addressing the problem of onset time estimation for regional arrivals. Most methods proposed thus far attempt to find the first point where the statistical properties of the seismic trace change. This is difficult or next to impossible with the often emergent regional arrivals. Instead, we are advocating a methodology based on the cumulative sum (CUSUM) of various statistics. Superposing a linear trend on the cumulative sum can make the changes in the trend of CUSUM to become minima of the resulting function.

In this report we present test results on various non-conventional signal processing approaches as applied to data from regional seismic arrays. In particular, an adaptive approach for automatic identification of regional arrivals was tested to (Der et al 1993). This method was designed to circumvent some difficulties that plagued previous attempts of 3-component polarization analyses for regional arrival identification. In particular, the methodology is designed to avoid complications due to signal distortion by near sensor geology and complex arrivals made up of superpositions of multiple independent signal components. The idea is to replace time delay operators and assumed particle motion patterns used in deterministic signal processing with empirically computed sets of transfer functions using a learning set of relatively high S/N events. The application of this approach requires more than three sensor outputs (such as a 3-component combination plus some extra array sensors). We have tested both a frequency domain and a time domain approach to this algorithm. Thus far the frequency-domain version has reached a further stage of development. The methodology appears to be an attractive alternative to conventional array processing methods in quickly identifying and discriminating various arrivals from the same source region, or similar arrivals from different source regions at a small array. We are also addressing the problem of onset time estimation for regional arrivals. Most methods proposed thus far attempt to find the first point where the statistical properties of the seismic trace change. This is difficult or next to impossible with the often emergent regional arrivals. Instead, we are advocating a methodology based on the cumulative sum (CUSUM) of various statistics. Superposing a linear trend on the cumulative sum can make the changes in the trend of CUSUM to become minima of the resulting function.